Focus on cvat vulnerabilities and metrics.
Last updated: 08 Mar 2025, 23:25 UTC
This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with cvat. We track both calendar-based metrics (using fixed periods) and rolling metrics (using gliding windows) to give you a comprehensive view of security trends and risk evolution. Use these insights to assess risk and plan your patching strategy.
For a broader perspective on cybersecurity threats, explore the comprehensive list of CVEs by vendor and product. Stay updated on critical vulnerabilities affecting major software and hardware providers.
Total cvat CVEs: 5
Earliest CVE date: 14 Dec 2021, 19:15 UTC
Latest CVE date: 10 Sep 2024, 15:15 UTC
Latest CVE reference: CVE-2024-45393
30-day Count (Rolling): 0
365-day Count (Rolling): 3
Calendar-based Variation
Calendar-based Variation compares a fixed calendar period (e.g., this month versus the same month last year), while Rolling Growth Rate uses a continuous window (e.g., last 30 days versus the previous 30 days) to capture trends independent of calendar boundaries.
Month Variation (Calendar): 0%
Year Variation (Calendar): 0%
Month Growth Rate (30-day Rolling): 0.0%
Year Growth Rate (365-day Rolling): 0.0%
Average CVSS: 1.02
Max CVSS: 5.1
Critical CVEs (≥9): 0
| Range | Count |
|---|---|
| 0.0-3.9 | 4 |
| 4.0-6.9 | 1 |
| 7.0-8.9 | 0 |
| 9.0-10.0 | 0 |
These are the five CVEs with the highest CVSS scores for cvat, sorted by severity first and recency.
Computer Vision Annotation Tool (CVAT) is an interactive video and image annotation tool for computer vision. An attacker with a CVAT account can access webhook delivery information for any webhook registered on the CVAT instance, including that of other users. For each delivery, this contains information about the event that caused the delivery, typically including full details about the object on which an action was performed (such as the task for an "update:task" event), and the user who performed the action. In addition, the attacker can redeliver any past delivery of any webhook, and trigger a ping event for any webhook. Upgrade to CVAT 2.18.0 or any later version.
Computer Vision Annotation Tool (CVAT) is an interactive video and image annotation tool for computer vision. Starting in version 2.2.0 and prior to version 2.14.3, if an attacker can trick a logged-in CVAT user into visiting a malicious URL, they can initiate a dataset export or a backup from a project, task or job that the victim user has permission to export into a cloud storage that the victim user has access to. The name of the resulting file can be chosen by the attacker. This implies that the attacker can overwrite arbitrary files in any cloud storage that the victim can access and, if the attacker has read access to the cloud storage used in the attack, they can obtain media files, annotations, settings and other information from any projects, tasks or jobs that the victim has permission to export. Version 2.14.3 contains a fix for the issue. No known workarounds are available.
Computer Vision Annotation Tool (CVAT) is an interactive video and image annotation tool for computer vision. CVAT allows users to supply custom endpoint URLs for cloud storages based on Amazon S3 and Azure Blob Storage. Starting in version 2.1.0 and prior to version 2.14.3, an attacker with a CVAT account can exploit this feature by specifying URLs whose host part is an intranet IP address or an internal domain name. By doing this, the attacker may be able to probe the network that the CVAT backend runs in for HTTP(S) servers. In addition, if there is a web server on this network that is sufficiently API-compatible with an Amazon S3 or Azure Blob Storage endpoint, and either allows anonymous access, or allows authentication with credentials that are known by the attacker, then the attacker may be able to create a cloud storage linked to this server. They may then be able to list files on the server; extract files from the server, if these files are of a type that CVAT supports reading from cloud storage (media data (such as images/videos/archives), importable annotations or datasets, task/project backups); and/or overwrite files on this server with exported annotations/datasets/backups. The exact capabilities of the attacker will depend on how the internal server is configured. Users should upgrade to CVAT 2.14.3 to receive a patch. In this release, the existing SSRF mitigation measures are applied to requests to cloud providers, with access to intranet IP addresses prohibited by default. Some workarounds are also available. One may use network security solutions such as virtual networks or firewalls to prohibit network access from the CVAT backend to unrelated servers on your internal network and/or require authentication for access to internal servers.
CVAT is an opensource interactive video and image annotation tool for computer vision. Versions prior to 2.0.0 were found to be subject to a Server-side request forgery (SSRF) vulnerability. Validation has been added to urls used in the affected code path in version 2.0.0. Users are advised to upgrade. There are no known workarounds for this issue.
It was found that the fix to address CVE-2021-44228 in Apache Log4j 2.15.0 was incomplete in certain non-default configurations. This could allows attackers with control over Thread Context Map (MDC) input data when the logging configuration uses a non-default Pattern Layout with either a Context Lookup (for example, $${ctx:loginId}) or a Thread Context Map pattern (%X, %mdc, or %MDC) to craft malicious input data using a JNDI Lookup pattern resulting in an information leak and remote code execution in some environments and local code execution in all environments. Log4j 2.16.0 (Java 8) and 2.12.2 (Java 7) fix this issue by removing support for message lookup patterns and disabling JNDI functionality by default.